Results 61 to 70 of about 335,663 (179)
Unsupervised Steganalysis Based on Artificial Training Sets
, 2016 In this paper, an unsupervised steganalysis method that combines artificial training setsand supervised classification is proposed. We provide a formal framework for unsupervisedclassification of stego and cover images in the typical situation of ...
Lerch-Hostalot, Daniel, Megías, David
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Embeddability and universal theory of partially commutative groups
, 2015 The first part of the paper centers in the study of embeddability between partially commutative groups. In [KK], for a finite simplicial graph $\Gamma$, the authors introduce an infinite, locally infinite graph $\Gamma^e$, called the extension graph of $\
Casals-Ruiz, Montserrat
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Optimal Embedding of Functions for In-Network Computation: Complexity Analysis and Algorithms
, 2015 We consider optimal distributed computation of a given function of distributed data. The input (data) nodes and the sink node that receives the function form a connected network that is described by an undirected weighted network graph.
Limaye, Nutan +2 more
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Group Embeddings with Algorithmic Properties [PDF]
Communications in Algebra, 2015 We show that every countable group H with solvable word problem (=computable group) can be subnormally embedded into a 2-generated group G which also has solvable word problem. Moreover, the membership problem for H < G is also solvable. We also give estimates of time and space complexity of the word problem in G and of the membership problem for H &
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Task-Optimized Word Embeddings for Text Classification Representations
Frontiers in Applied Mathematics and Statistics, 2020 Word embeddings have introduced a compact and efficient way of representing text for further downstream natural language processing (NLP) tasks. Most word embedding algorithms are optimized at the word level.
Sukrat Gupta +3 more
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Efficient Algorithms for Embedded Tactile Data Processing
, 2022 This chapter presents a survey of the existing algorithms and tasks applied for tactile data processing. The presented algorithms and tasks include machine learning, deep learning, feature extraction, and dimensionality reduction. Moreover, this chapter provides guidelines for selecting appropriate hardware platforms for the algorithm’s implementation.
Younes H. +4 more
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Deep Metric Learning via Lifted Structured Feature Embedding
, 2015 Learning the distance metric between pairs of examples is of great importance for learning and visual recognition. With the remarkable success from the state of the art convolutional neural networks, recent works have shown promising results on ...
Jegelka, Stefanie +3 more
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Service function chain embedding algorithm with wireless multicast in mobile edge computing network
Tongxin xuebao, 2020 To resolve the excessive system overhead and serious traffic congestion in user-oriented service function chain (SFC) embedding in mobile edge computing (MEC) networks,a content-oriented joint wireless multicast and SFC embedding algorithm was proposed ...
Kan WANG +3 more
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An efficient histogram-preserving steganography based on block
EURASIP Journal on Image and Video Processing, 2018 In order to reduce the influence on cover image caused by embedding algorithm, while keeping the histogram characteristics of cover image, in this paper a histogram preserving steganography algorithm is proposed based on dividing a secret message into ...
Jie Cheng, Zhenzuo Chen, Rener Yang
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SAR Algorithms for Embedded Platforms
, 2021 Radar is an electromagnetic remote sensing system for the detection of reflecting targets. By transmitting pulses of very short duration, high resolution in the range direction can be easily achieved. However, traditional radar cannot distinguish between two side-by-side targets that are illuminated by the antenna beam at the same time.
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